Manjunath Bagewadi — AI Researcher

visit personal portfolio: www.manjunathbagewadi.in I’m a AI Practitioner with 9+ years of experience delivering end-to-end machine learning, deep learning, and generative AI solutions that drive measurable business outcomes. My expertise spans manufacturing analytics, pharma, telecom, and finance, where I bridge the gap between technical innovation and strategic business value. What I Do: 1. Manufacturing Optimization: Designed ML pipelines and dashboards that reduced unplanned downtime by 25%, improved batch throughput by ~2M units annually, and increased process efficiency by 15–20% across multiple sites. 2. Predictive & Prescriptive Analytics: Built time-series anomaly detection, hybrid regression + neural network soft sensors, and reinforcement-learning-based recommendation engines to enable data-driven decisions in real time. 3. Cloud-Native AI: Deployed scalable solutions on AWS, Azure, and Domino, leveraging CI/CD, modular code design, and explainable AI (SHAP, LIME) to ensure transparency and trust. 4. Generative AI & Automation: Applied LangChain, and AI agents to accelerate analytics workflows and prototype next-gen automation tools for manufacturing analytics. 5. Research & Innovation: Co-authored a patent-filed ML + process-mining prototype at Siemens, Eli lilly and secured Top 15/6000 rank in TechGig Alexa Hackathon for conversational AI innovation. Core Strengths 1. ML/DL Expertise: Regression, Tree-based models, PCA, SVM, ANN, CNNs, Autoencoders, HMMs, RL, Time-Series Forecasting 2. GenAI & Agentic AI: RAG, AI Agents, MCP applications for intelligent automation 3. Cloud & MLOps: AWS SageMaker, Azure ML Studio, Domino, CI/CD Pipelines 4. Visualization: Dash, Plotly, PowerBI— turning insights into actionable, interactive dashboards 5. Business Translation: Stakeholder engagement, solution design, and domain expertise in pharma, manufacturing, and healthcare analytics Selected Projects: Github presence of few hobby projects: Medical Waste Detection (YOLO) – CNN-based object detection for medical waste segregation Automatic Bug Triaging – Patent-filed ML solution for automated bug resolver recommendations Cardiac MRI Analysis – CNN/Autoencoder-based medical imaging solution Alexa skill https://github.com/manjunathsept11 I thrive at the intersection of AI innovation, business strategy, and team collaboration — designing solutions that don’t just work technically, but deliver measurable ROI. Always open to connecting with fellow professionals, sharing knowledge, and exploring opportunities to make AI a competitive advantage.

Stackforce AI infers this person is a Data Science and AI expert with a focus on healthcare and manufacturing analytics.

Location: Bangalore, Karnataka, India

Experience: 11 yrs 4 mos

Skills

Machine Learning
Data Science

Career Highlights

9+ years of experience in AI and machine learning.
Expertise in manufacturing, pharma, telecom, and finance analytics.
Co-authored a patent for innovative ML solutions.

Work Experience

Eli Lilly and Company

Principal Data Scientist (1 yr 8 mos)

Senior Associate Consultant (2 yrs)

Sr Associate Manager - Data Scientist (1 yr 9 mos)

AT&T

Data Scientist (3 yrs 6 mos)

ShieldSquare

Machine Learning Engineer SDE (3 mos)

Siemens Technology India

Research Engineer (8 mos)

Intern (10 mos)

Tata Consultancy Services

Assistant System Engineer (8 mos)

Education

Master’s Degree at Manipal Institute of Technology

Bachelor’s Degree at Visvesvaraya Technological University

High School at Jawahar Navodaya Vidyalaya Belgaum

Manjunath Bagewadi

AI Researcher

Bangalore, Karnataka, India11 yrs 4 mos experience

AI ML PractitionerAI Enabled

Key Highlights

9+ years of experience in AI and machine learning.
Expertise in manufacturing, pharma, telecom, and finance analytics.
Co-authored a patent for innovative ML solutions.

Stackforce AI infers this person is a Data Science and AI expert with a focus on healthcare and manufacturing analytics.

Contact

Skills

Core Skills

Machine LearningData Science

Other Skills

AIAWSAdobe AuditionAdobe PhotoshopApache SparkArtificial Intelligence (AI)Association Rule MiningAzureBig DataBlockchainBootstrapComputer VisionContinuous IntegrationD3.jsDaVinci Resolve

About

Experience

11 yrs 4 mos

Total Experience

2 yrs 3 mos

Average Tenure

Current Experience

Eli lilly and company

3 roles

Principal Data Scientist

Promoted

Feb 2024 – Oct 2025 · 1 yr 8 mos · Bengaluru, Karnataka, India

Senior Associate Consultant

Promoted

Feb 2022 – Feb 2024 · 2 yrs · Bengaluru, Karnataka, India

Sr Associate Manager - Data Scientist

May 2020 – Feb 2022 · 1 yr 9 mos · Bengaluru, Karnataka, India

Working on use cases which focuses on Industry 4.0, manufacturing analytics and healthcare analytics.
1. Anomaly Detection
2. Preventive maintenance and Downtime prediction
3. AI Vision
4. Supply chain analytics
5. Process mining
Technologies: AWS, Domino, Azure , Time series analysis, Data science principles , DL , Ml , Vizualization, EDA etc

AWSDominoAzureTime series analysisData science principlesDeep Learning+4

At&t

Data Scientist

Sep 2016 – Mar 2020 · 3 yrs 6 mos · Bengaluru, Karnataka, India

1 . Virtual Ticket Management : Company: AT&T (AI/ML/ Big data analytics / Hive Project)
The Virtual Ticket Management involves analysis on ticket data of AT&T services. Which sources data from BMP and AOTS. Which contains details of ticket and its resolution steps. The analytics involves to find patterns in ticket resolution life cycle and time to resolve ticket.
a. Estimating time for a new ticket to reach its next resolution step
b. Estimating next milestone for a ticket under resolution
c. Predicting the similar tickets in the past for upcoming tickets
2. Medical Waste object Detection using YOLO (CNN )’: (AI/ML Project)
https://github.com/manjunathsept11/Medical-Waste-Object-Detection-Using-YOLO
3. AWS ALexa : https://github.com/manjunathsept11/Short-News-Alexa-Skill
4. CARDIAC MRI IMAGE ANALYSIS - Identifying Left Ventricle using Deep learning:(CNN, Auto Encoders) (AI/ML Project)
https://github.com/manjunathsept11/CARDIAC-MRI-IMAGE-ANALYSIS-Identify-Left-Ventricle-Using-Deep-Learning
5. “AWS Exploration” Company: AT&T
Description: Explored the cloud platform AWS services keeping AI in focus. Explored on Sagemaker, Polly, Deeplense, Transcribe, Machine learning, EC2, Cloud formation. Following are the POC works done in AWS.
a. Built Alexa skills, which involves writing python lambda serverless functions, interacting with third party external apis, preparing utterances and intents
b. Built lex chatbots in aws. Build voice and text based web and android chat application which interacts with aws lex.
Responsibilities:
a. Analyzing the use case with proper domain context and Researching on various Machine learning approaches to solve use case.
b. Exploratory analysis on data, written python adapters for data munging operation on raw data to transform into model consumable data and modelling.
c. Parameter tuning and validation for better results
d. Python Scripts to implement solution approach and deployment.

AIMLBig DataAWSPythonData Analysis+2

Shieldsquare

Machine Learning Engineer SDE

Mar 2016 – Jun 2016 · 3 mos · Bengaluru, Karnataka, India

1. Worked on Association rule mining techniques. Finding sequencial pattens in robotic activities for website hits.
2. Python projects.
3. Setting up devops culture using Continuous Integration like Jenkins.

PythonAssociation Rule MiningDevOpsContinuous Integration

Siemens technology india

2 roles

Research Engineer

Apr 2015 – Dec 2015 · 8 mos · Banglore

1. Project: “Automatic Bug Triaging” Company: Siemens ( ML / AI Project )
Description: Automatic bug triaging is a research prototype, a decision support platform for guiding a bug triager for resolver recommendation using textual and non textual features. This automates the bug triaging. It involves machine learning, data mining, data science, visualization and information retrieval concepts.
2. Defect Prediction” Company: Siemens ( ML / AI Project )
Description: Developing a platform for bug prediction where the bug proneness of a files and components of a project can be predicted. This will help stake holders to allocate resources and estimations properly. It involves machine learning, data mining and visualization concepts.
Platform: Java, j2ee, Mysql , Bootstrap, Jquery, D3.js ,IBM Clear quest
Responsibilities:
1. Analyzing and clean-up activities on siemens product line bug data (i.e ITS data).
2. Exploratory analysis and process mining on data.
3. Building optimized supervised machine learning classification models.
4. Building adapters for Data Munging and NLP operations.
5. Training models using different machine learning classifier algorithms and ensemble results.
6. Creating GUI using bootstrap, Jquery, jsp, servlets and visualizations using D3.js and chart.js

Machine LearningData MiningVisualization

Intern

Jun 2014 – Apr 2015 · 10 mos · Banglore

Tata consultancy services

Assistant System Engineer

Nov 2012 – Jul 2013 · 8 mos · Pune

Project: Multi Banking system Company: TCS
Description: Developed during TCS ILP training. It’s a web application, which is a common portal to all banks and customers to access their bank accounts and manage the accounts. The banks and customers get register to the portal and they can do the transactions like FD, RD, Transfer money, Service requesting, transfer within same bank accounts, transfer between different bank accounts etc in a single portal. Implemented in MVC architecture.
Environment: Java servlet, JSP, Oracle9 in Eclipse IDE